Compact Context

Quick Summary

Goal: Compress conversation context to optimize token usage while preserving critical information.

Thin alias. /​compact is the user-facing entry point to the Compress strategy (Strategy #3) owned by context-optimization. That skill is disable-model-invocation: true (not directly user-invocable), so this command is the canonical way to trigger a manual compaction. /​compact is also a CLI-native command — this alias keeps the harness-specific preservation guidance attached to it without re-implementing the compress logic, which lives once in context-optimization.

Workflow:

1. Analyze — Identify essential vs. expendable context
2. Compress — Remove redundant tool outputs / repeated searches / verbose logs; summarize findings
3. Verify — Ensure critical decisions, files modified, and current task state are preserved

Key Rules:

• Canonical compress protocol + the full 4-strategy framework (write/​select/​compress/​isolate) + token thresholds live in context-optimization — this skill is the command surface only
• Preserve: decisions made, files modified, current task state, error/​stack traces, todos
• Use /​compact at natural breakpoints (after commits, PR), not mid-task

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Compact Context

Proactively compress the current conversation context to optimize token usage. This is the user-invocable alias for context-optimization's Compress strategy.

When to Use

• Before starting a new task in a long session
• When working on multiple unrelated features
• At natural workflow checkpoints (after commits, PR creation)
• When the context indicator shows high usage (≥100K tokens → required; ≥150K → critical)

Instructions

1. Run the Pre-Compaction Preservation Checklist — canonical in .claude/​skills/​context-optimization/​SKILL.md (Strategy #3 → "Pre-Compaction Preservation Checklist"): branch + uncommitted-changes status, active file paths, error messages / stack traces, key decisions + rationale, pending todos.
2. Compress — summarize completed work + key decisions; clear redundant history (old exploration, superseded plans); keep active file paths, current task, blockers.
3. Restate objective — after compacting, briefly restate the current objective and confirm critical file paths are still accessible.

For the full context-management framework (Write / Select / Compress / Isolate strategies, context-anchor protocol, memory commands, token-efficient patterns), see context-optimization.

Related Commands

• context-optimization — full 4-strategy context-management framework (canonical owner)
• /​checkpoint — save analysis context to an external file before compaction
• /​recover — restore workflow context from the latest checkpoint

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[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

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AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path. Keep domain concepts out of generic/​shared/​infrastructure layers. A reusable layer (shared library, framework, infra module) must reference NO consumer-specific domain concept — tenant/​customer/​product IDs, business entities, feature rules. The leak compiles and runs, so it passes review silently while coupling the "reusable" layer to one consumer. Push domain fields/​logic down into the consumer via subclass or composition.

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Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

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MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

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MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

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Closing Reminders

• MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
• MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
• MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
• MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.